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Numerous studies have shown that minority workers are disadvantaged in the labour market due to stereotypes and discrimination. However, published research on résumé screening has overlooked the effects of multiple social categorisations pertaining to candidates' gender, education and origin. This study addresses this gap and examines whether the gender, the level of education and the national origin cues mentioned in the résumé affect the perceived employability of candidates.

This study employs an experimental between-subjects factorial design in that 12 résumés varying in gender, education and national origin were rated by 373 Portuguese working adults.

The results documented a gender premium as women were favoured in interpersonal and job skills but not in job suitability, and an education premium, since higher educated candidates were preferred despite their gender and origin. No meaningful interactions for gender × education × national origin were observed, which suggests that ingroup favouritism and outgroup discrimination in résumé screening can be averted.

The findings endorse a multidimensional view of perceived employability by investigating candidates' skills and job suitability from the viewpoint of the decision-makers, which extends our understanding of résumé-screening discrimination. This is critical to prevent hiring discrimination at an earlier career stage, which can increase youth employment and enhance the integration in the labour market of local minorities such as women, inexperienced workers and second-generation immigrants.

This study aims to propose a data-driven approach, based on open-source tools, that makes it possible to understand customer satisfaction of the accommodation offer of a whole country.

The method starts by extracting information from all hotels of Portugal available at TripAdvisor through Web scraping. Then, a support vector machine is adopted for modeling the TripAdvisor score, which is considered a proxy of customer satisfaction. Finally, knowledge extraction from the model is achieved using sensitivity analysis to unveil the influence of features on the score.

The model of the TripAdvisor score achieved a mean absolute percentage error of around 5 per cent, proving the value of modeling the extracted data. The number of rooms of the unit and the minimum price are the two most relevant features, showing that customers appreciate smaller and more expensive units, whereas the location of the hotel does not hold significant relevance.

National tourist offices can use the proposed approach to understand what drives tourists’ satisfaction, helping to shape a country’s strategy. For example, licensing new hotels may take into account the unit size and other characteristics that make it more attractive to tourists. Furthermore, the procedure can be replicated at any time and in any country, making it a valuable tool for data-driven decision support on a national scale.

This paper aims to characterize the type of support provided to victims of violence against women and domestic violence (VAWDV) during the first lockdown, assessing the training of professionals to use remote support (RS).

This cross-sectional study involves a sample of 196 support professionals, mainly women (91.8%) and who integrate the Portuguese National Support Network for victims of domestic violence (NSNVDV) (Mean age = 36.49; SD = 10.52).

Telephone emerges as the main RS communication media used in the lockdown (43.9%) and the emergency state periods (57.1%). Participants reported to have never used any social applications (41.8% vs 41.8%) or videoconference (46.4% vs 58.2%), in both periods assessed, i.e. lockdown and emergency state, respectively, and 82.7% assumed to have no training with RS to assist VAWDV victims. However, support professionals recognized several advantages in using RS such as dealing with isolation, reducing inhibition, fear and shame and in promoting the victims’ empowerment.

Given the exploratory nature of this study, only descriptive analyzes were conducted.

During the COVID-19 pandemic, little is known about effective RS given by professionals to victims of VAWDV in the Portuguese context. The paper aims to add knowledge to the studied field.

This study aims to present a model drawn on both the extension of the unified theory of acceptance and use of technology (UTAUT2) and the perceived value for explaining consumer behavior toward mobile hospitality services (MHS) from two perspectives: intention to use and recommendation.

The partial least square (PLS) was applied to data gathered from 348 validated responses to a survey to test a number of research hypotheses.

Results found that the proposed conceptual model explains 62 per cent of the intention to use of MHS and 51 per cent of the variation in the recommendation. Perceived value plays a role in explaining both the intention to use and recommend MHS, with both constructs also helping in explaining behavior intention, to which effort expectancy, facilitating conditions and performance expectancy also contribute.

This research goes beyond perceived value by combining it with a cornerstone model, UTAUT2, used in technology adoption studies. The paper addresses updated MHS that include but are not limited to mobile hotel reservations.

National tourism offices worldwide implement marketing strategies to influence tourists’ choices. However, there is more than meets the eye when it comes to choosing a city as a tourism destination. The purpose of this paper is to answer which are the characteristics that play a key role in room occupancy.

Diverse characteristics such as the city offer, demographics, natural amenities (e.g. number of beaches) and also politics (e.g. type of government) are combined into a decision tree model to unveil the relevance of each in determining room occupancy. The empirical experiments used data known in 2015 from 43 cities from Europe and the rest of the World to model room occupancy rate in 2016.

While the seasonality effect plays the most significant role, other less studied features such as the type of political party prior to current government were found to have an impact in room occupancy.

This study unveiled that center–right and right governments are generally more sensitive to promote its city as a tourism destination.

Airbnb Experiences is a new type of service launched by Airbnb in November 2016, where users can offer travellers a wide range of activities. This study devotes attention to analysing customer feedback expressed in online reviews published in Airbnb to evaluate those experiences.

A total of 1,110 reviews were collected from 12 categories, including 111 experiences, resulting in 10 reviews per experience. First, the sentiment score was computed based on the text of the reviews. Second, 17 quantitative features encompassing user, Airbnb experience and review information were used to model the score through a support vector machine. Third, a sensitivity analysis was performed to extract knowledge on the most relevant features influencing the sentiment score.

Tourists writing online reviews are not only influenced by their tourist experience but also by their own online experience with the booking and online review platform. The number of reviews made by the user accounted for more than 20 per cent of relevance, while users with more reviews tended to grant more positive reviews.

Current literature is enhanced with a conceptual model grounded on existing studies that assess tourist satisfaction with tour services. Both services online visibility and user characteristics have shown significant importance to tourist satisfaction, adding to the existing body of knowledge.

Social media has become the main venue for users to express their opinions and feelings, generating a vast number of available and valuable data to be scrutinized by researchers and marketers. This paper aims to extend previous studies analyzing social media reviews through text mining and sentiment analysis to provide useful recommendations for management in the restaurant industry.

The Lexalytics, a text mining artificial intelligence tool, is applied to analyze the text of the online reviews of the restaurants in a touristic Dutch village extracted from the most frequently used social media platforms focusing on the four restaurant quality factors, namely, food and beverage, service, atmosphere and value.

The findings of this research are presented by the identified key themes with comparisons of the customers’ review sentiment between a selected restaurant, Zwaantje, vis-à-vis its bench-mark restaurants set by a specific approach under the abovementioned quality dimensions, in which the food and beverage and service are the most commented by customers. Results demonstrate that text mining can generate insights from different aspects and that the proposed approach is valuable to restaurant management.

The paper provides a relatively big scale in numbers and resources of social media reviews to further explore the most important service dimensions in the restaurant industry in a specific tourist area. It also offers a useful framework to apply the text mining business intelligence tool by comparison of peers for local small business restaurant practitioners to improve their management skills beyond manually reading social media reviews.

The purpose of this study is to contribute with new insights into the nature, dimensionality and measurement of the core essence of the small city boutique hotel (SCBH), something which has been limited in the literature to date. It further explores the conceptual relationships of SCBH with other constructs, providing greater understanding of the nature of these specific conceptual associations and showing that the SCBH scale exhibits construct validity.

This study followed the Churchill’s paradigm to methodologically design the study and develop the scale. Based on an exploratory qualitative inquiry (one focus group and ten interviews) and quantitative assessment (two surveys), support was found for a three-dimensional scale.

Results support the proposed measures of the scale (dream, hospitality and style) in terms of construct, convergent, discriminate, nomological and predictive validity. The findings also suggest that while authenticity acts as a SCBH antecedent, pleasant arousal and preference represent SCBH consequences.

By developing and validating a SCBH scale for city destination, this study addresses an identified literature gap. Specifically, it conceptualizes SCBH as guests’ perception about core characteristics of SCBHs located in the city.

The main objective of this study is the application of portfolio analysis, as an instrument of decision‐making support, to the selection of priority market segments for Portugal. The results obtained validate the use of competitiveness and attractiveness as tools for the selection and management of generating markets for a tourist destination. The selection of factors to calculate the values of competitiveness and attractiveness was based on a review of the literature on destination competitiveness, portfolio models in general and studies applied to tourist destinations. The relative importance of the factors was determined after consultation with a panel of experts. Cronbach’s alpha test was used to verify the scale reliability. Tourist arrivals, tourists stays, foreign exchange revenue and bednights in hotel units were used as performance indicators of generating countries. Correlation and multiple linear regression analysis were used to study the relation between attractiveness and competitiveness and performance.

Diabetes is a chronic and challenging disease and requires personal daily self-management decisions and skills. For that, it is necessary that patients have sufficient information and health literacy to make the right choices and decisions in their self-care. Sequentially, health literacy has great relevance and influence in the daily lives of people with diabetes, since it encompasses the necessary skills to manage disease and health. Health literacy can be a relevant factor to consider when tackling diabetes self-management. Thus, for the prevention and treatment of diabetes, it is essential to promote individual health literacy. The quality of communication and patient-centred communication style seems to be a key aspect for the health literacy.